Package: PCAmixdata 3.1

PCAmixdata: Multivariate Analysis of Mixed Data

Implements principal component analysis, orthogonal rotation and multiple factor analysis for a mixture of quantitative and qualitative variables.

Authors:Marie Chavent [aut, cre], Vanessa Kuentz [aut], Amaury Labenne [aut], Benoit Liquet [aut], Jerome Saracco [aut]

PCAmixdata_3.1.tar.gz
PCAmixdata_3.1.zip(r-4.5)PCAmixdata_3.1.zip(r-4.4)PCAmixdata_3.1.zip(r-4.3)
PCAmixdata_3.1.tgz(r-4.4-any)PCAmixdata_3.1.tgz(r-4.3-any)
PCAmixdata_3.1.tar.gz(r-4.5-noble)PCAmixdata_3.1.tar.gz(r-4.4-noble)
PCAmixdata_3.1.tgz(r-4.4-emscripten)PCAmixdata_3.1.tgz(r-4.3-emscripten)
PCAmixdata.pdf |PCAmixdata.html
PCAmixdata/json (API)

# Install 'PCAmixdata' in R:
install.packages('PCAmixdata', repos = c('https://chavent.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/chavent/pcamixdata/issues

Datasets:
  • decathlon - Performance in decathlon
  • dogs - Breeds of Dogs data
  • flower - Flower Characteristics
  • gironde - Gironde
  • protein - Protein data
  • vnf - User satisfaction survey with 1232 individuals and 14 questions
  • wine - Wine

On CRAN:

8.19 score 8 stars 6 packages 82 scripts 1.3k downloads 11 mentions 10 exports 0 dependencies

Last updated 2 years agofrom:428226c55b. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 03 2024
R-4.5-winOKNov 03 2024
R-4.5-linuxOKNov 03 2024
R-4.4-winOKNov 03 2024
R-4.4-macOKNov 03 2024
R-4.3-winOKNov 03 2024
R-4.3-macOKNov 03 2024

Exports:MFAmixPCAmixPCArotrecodrecodqualrecodquantsplitgroupssplitmixsupvartab.disjonctif.NA

Dependencies:

How to use the PCAmixdata Package

Rendered fromPCAmixdata.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2019-04-04
Started: 2017-08-28

Supplementary Observations, Variables or Groups

Rendered fromsupplementary.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2017-08-28
Started: 2017-08-28